Potential New Roles in Software in the Age of AI

The following is an excerpt from the book Vibe Coding: Building Production-Grade Software With GenAI, Chat, Agents, and Beyond by Gene Kim and Steve Yegge.

Dr. Matt Beane, author of The Skill Code who coined the “novice optional” problem has been studying how automation reshapes work. He shared some compelling stories with us that paint a vivid picture of how new roles emerge when new, and often resoundingly flawed, technologies arrive. His research in settings like automated warehouses offers us a potential glimpse of the changes that will sweep through software development with AI. It turns out, the current “janky” phase of a new technology is precisely where new skills are forged and new career paths are blazed. Some of this research will be published in an upcoming academic journal, but he generously shared two jaw-dropping stories with us after reading a draft of this book.

First, warehouses were being newly equipped with AI-powered robots for pick-and-pack operations. As Dr. Beane described, these early robots were often unreliable. While some might see this as a problem, it created an unexpected opportunity. He told us about entry-level workers, sometimes on the graveyard shift, who became “hidden innovators.” 

One non-English-speaking worker, faced with confusing error messages on a robot, ingeniously suggested using icons instead—a valuable UX insight, because many of her fellow workers could not read English. These folks were performing essential “operational glue” work, troubleshooting and improving systems, often without their managers (or themselves) fully recognizing the valuable technical skills they were building. As a leader, be on the lookout for people doing this type of ingenious problem-solving. Some of the best discoveries can come from a junior engineer who has been quietly experimenting.

The catch, Dr. Beane pointed out, is that this burgeoning talent is often overlooked. In many cases, supervisors took the credit for these grassroots innovations, or the insights were lost altogether. He quoted one senior manager who lamented that in their facility, “Talent flows through this building like water.” 

This is a critical lesson for us in the software world as we integrate AI. If you’re not actively looking for and nurturing those individuals who are wrestling with AI’s quirks, you may be missing out on your most potent source of practical improvements and your next generation of AI-savvy team members. These are the people who, through sheer necessity, are figuring out how to make AI effective, even when it occasionally tries to delete your repo.

Then there’s the flip side: What happens when this emergent talent is recognized and cultivated. Dr. Beane shared another story from a startup developing advanced RHLF-trained robots. They hired their initial robot operators with a job ad asking, “Do you like to play video games?” These weren’t seasoned engineers; they were individuals comfortable with interfaces and rapid iteration. Placed in direct control of the robots, they transcended operating them and became integral to the engineering sprints. 

They identified critical failure modes and proposed game-changing features, like adding multiple “waypoints” for the robot arms (the resting position when it was idle), which dramatically boosted throughput. These “drivers” rapidly upskilled, moving into roles in UX, data science, and mechatronics—jobs that often “had no name” initially and for which they had no prior formal qualifications. Many ended up with six-figure salaries, demonstrating a powerful FAAFO effect on their careers: they moved fast, hurdled ambitious technical challenges, worked autonomously or in small, highly effective teams, found the process fun and engaging, and created new optionality for themselves and the company.

These stories from the front lines of robotic automation parallel what we’re seeing with vibe coding and AI. The software developers, product managers, and curious business users who are currently “driving” AI tools—wrestling with prompts, debugging AI-generated code, figuring out how to integrate AI into real-world workflows—are in the same position as those robot operators and warehouse innovators. They’re developing critical, often tacit, knowledge. As AI becomes more integrated into our software kitchens, we believe we’ll see a flourishing of these new, hybrid roles, born from the practical realities of making AI deliver value. The people who master this human–AI collaboration will be the ones shaping the future.

Dr. Beane’s research, and our own experiences, suggest several types of roles that could well become more prominent:

• Product Prototyper: Product managers picking up tools to hand over prototypes to developers, or apt developers picking up product management.
• Platform Designer: One-third product management, one-third designer, one-third systems infrastructure engineer, building user platforms for ultimate customizability.
• Fleet Fixer: Overseeing multiple AI systems, intervening when needed.
• Agent Expert: Domain experts who build and maintain domain agents.
• Fleet Supervisor: Directing multiple AI systems, designing interaction structures.
• Platform Engineer: Pushes up the stack, makes it more and more deterministic, lets you push more fuzzy stuff safely via sandboxing and guardrails.
• Apex Builder: Converts vibe-coded prototypes into hardened products; fixes legacy enterprise messes made during AI migrations.

The next chapter of your career may involve these new hybrid specializations. The future belongs not to AI alone, nor exclusively to human specialists—but to those creative visionaries who can orchestrate powerful teams composed of both. 

For more insights on effective AI-assisted development, check out Kim and Yegge’s new book Vibe Coding and their podcast Vibe Coding with Steve and Gene on YouTube.

- About The Authors

Gene Kim

Gene Kim has been studying high-performing technology organizations since 1999. He was the founder and CTO of Tripwire, Inc., an enterprise security software company, where he served for 13 years. His books have sold over 1 million copies—he is the WSJ bestselling author of Wiring the Winning Organization, The Unicorn Project, and co-author of The Phoenix Project, The DevOps Handbook, and the Shingo Publication Award-winning Accelerate. Since 2014, he has been the organizer of DevOps Enterprise Summit (now Enterprise Technology Leadership Summit), studying the technology transformations of large, complex organizations.

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Steve Yegge

Steve Yegge is an American computer programmer and blogger known for writing about programming languages, productivity, and software culture for two decades. He has spent over thirty years in the industry, split evenly between dev and leadership roles, including nineteen years combined at Google and Amazon. Steve has written over a million lines of production code in a dozen languages, has helped build and launch many large production systems at big tech companies, has led multiple teams of up to 150 people, and has spent much of his career relentlessly focused on making himself and other developers faster and better. He is currently an Engineer at Sourcegraph working on AI coding assistants.

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